Description: Large-scale studies of abundance, occupancy (distribution) and species richness are widespread in ecology and management. Common examples are habitat or metapopulation studies, biogeography, monitoring programs or game species surveys. Such studies typically produce repeated counts or detection/non-detection data for many (e.g. >20) locations and interest is focused on spatial or temporal patterns. However, their interpretation is complicated, since not accounting for imperfect detectability of individuals, occupied areas, or species, leads to an underestimation of abundance, occupancy and species richness and possibly to the masking, or spurious detection, of patterns, e.g. trends, regional patterns, or habitat relationships.

This course presents some of the exciting new statistical models developed in recent years to estimate abundance, occupancy and species richness corrected for imperfect detection in large-scale surveys, for abundance, see Royle and Nichols, Ecology, 2003; Royle, Biometrics, 2004; Royle et al., Ecology, 2004; Dorazio et al., Biometrics, 2005; Royle and Link, Ecology, 2005; for occupancy: MacKenzie et al., Ecology, 2002, 2003; and for occupancy and species richness: Dorazio & Royle, JASA, 2005; Dorazio et al., Ecology, 2006. These models have great potential for ecology and management, but, with the exception of the MacKenzie occupancy model, have not yet been implemented in widely available computer programs such as program MARK and are not yet widely known among biologists and managers.

This course covers use and implementation of these models using R and WinBUGS, see attached PDF outline. Practical exercises form an important part of it. After the course, participants are expected to be able to conduct their own analyses of their large-scale data.

Cost for the 4-day workshop is 500 CHF (approx. 320 Euro or 380 US$) for academic and 700 CHF (approx. 450 Euro or 530 US$) for non-academic participants, with a reduction to 300 CHF for members of the organising institutes. This fee includes all course materials, facilities for the workshop, and morning and afternoon refreshments.

Participants: 20–25 people with an academic or ecological consulting background. We assume that participants have undergraduate-level knowledge of statistics. No prior knowledge of ML or Bayesian methods is assumed.